發(fā)布時間：2018-03-10 02:07

  本文選題：移動設備　切入點：人臉終端　出處：《計算機仿真》2017年10期 　論文類型：期刊論文

【摘要】：移動設備網(wǎng)絡安全下人臉終端身份識別,能夠高效保證用戶身份信息安全。人臉終端身份的認證,需要對人臉終端設備中內(nèi)存資源進行分配引導,對人臉最優(yōu)解集進行標注,完成身份識別。傳統(tǒng)方法采集人臉特征圖像并進行檢測和跟蹤,再匹配后臺數(shù)據(jù)庫人臉信息獲得識別結果,但忽略了對人臉最優(yōu)解集進行標注,導致識別精度偏低。提出基于人臉檢測識別的人臉終端身份識別方法。利用Adaboost改進多形態(tài)人臉檢測方法,根據(jù)膚色特征搜索出局部特征確定人臉方向,便于候選區(qū)域分割;基于識別信息差異性質(zhì)量及最近鄰分類法,對人臉終端設備中的人臉圖像流數(shù)據(jù)實現(xiàn)內(nèi)存資源分配引導,以提高臉部識別能力,對人臉最優(yōu)解集進行標注并且選擇出樣本集置于移動設備內(nèi)存中,實現(xiàn)移動設備網(wǎng)絡安全的人臉終端身份識別。實驗結果表明,利用提出認證方法能夠良好實現(xiàn)移動設備身份識別。
[Abstract]:Face terminal identity recognition under mobile device network security can effectively guarantee the security of user identity information. The authentication of face terminal identity requires the allocation of memory resources in the face terminal equipment and the labeling of the face optimal solution set. The traditional method collects face feature image, detects and tracks, then matches the background database face information to obtain the recognition result, but neglects to annotate the face optimal solution set. The method of face terminal identification based on face detection and recognition is put forward. Using Adaboost to improve the multi-morphological face detection method, the local features can be searched according to the skin color feature to determine the direction of face, which is convenient for candidate region segmentation. Based on the difference quality of recognition information and the nearest neighbor classification, the memory resource allocation of face image stream data in face terminal equipment is guided to improve the ability of face recognition. The face optimal solution set is annotated and the sample set is selected to be placed in the memory of the mobile device to realize the mobile device network secure face terminal identity recognition. Using the proposed authentication method, mobile device identification can be realized well.
【作者單位】： 濰坊科技學院;
【分類號】：TP391.41;TP393.08

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